The present invention is related to the field of computer generated modeling, and more specifically, to a technique for generating a personalized three-dimensional (3-D) face model from a sequence of two-dimensional (2-D) images of a person""s face.
Generation of a 3-D face model of a person involves mapping a real image of the face of the person onto a 3-D triangular mesh that has been shaped to have the same or similar geometry as the face of the person. 3-D triangular mesh refers to a connected set of triangular patches in 3-D whose corners form the nodes of the mesh. Each triangular patch in the 3-D mesh acquires its image data from an associated triangular region in the image of the face.
The methods disclosed in the prior art for generating a 3-D face model can be generally classified as those that involve (i) a fully manual process, (ii) a semi-automatic process and (iii) a fully-automatic process. In a fully manual process, every triangular patch of the 3-D mesh has to be manually mapped onto the image of the face according to the facial features of the face. Fully manual processes are labor intensive and time consuming because the number of triangular patches in the 3-D mesh could range from a hundred to several thousands.
There are known techniques for using markers to track selected facial features such as the eyebrows, ears, mouth and corners of the eyes.
Semi-automatic processes rely on automatically detecting or manually marking certain features on the face, such as eyes, nose and mouth, and initialize the 3-D mesh by an affine warping of a standard 3-D mesh based on the location of the detected facial features. However, a global affine transformation generally does not match the many local facial dimensions. Thus, the locations of the nodes are fine-tuned in a manual process for each person.
Fully automatic processes drastically reduce the time required to map an image onto a 3-D mesh. However, while hardware based fully automatic processes are very costly, software based fully automatic processes are very sensitive to the image data and thus may not consistently produce accurate 3-D face models.
In addition to a 3-D mesh that matches the geometry of the face, a composite image that contains facial image data from various viewing directions also needs to be constructed. In the prior art, the composite image is a mosaic (or sprite) image of the face that is produced either by a 3-D rotating camera or by stitching a number of 2-D images of the face. While the former process is very costly, the latter one is generally very inaccurate.
Hence, there is a need for a fast, inexpensive, and accurate method for generating the 3-D mesh and texture image for a face model. The present invention proposes a semi-automatic method for generating the 3-D mesh with minimal manual fine tuning. The present invention also proposes a simpler and more general technique for generating the texture image, that involves only concatenating and color blending the 2-D images of the face.
The present invention provides an improvement designed to satisfy the aferomentioned needs. Particularly, the present invention is directed to a computer program product for creating a 3-D face model from a plurality of 2-D images of a person""s face, by performing the steps of: (a) receiving the plurality of images of a person; (b) obtaining the geometry mesh by deforming a predefined standard 3-D triangular mesh based on the dimensions and relative positions of the person""s facial features; and (c) obtaining the texture image by compositing a plurality of 2-D images of the person taken from particular directions and modifying them in boundary regions to achieve seamless stitching of color for the 3-D face model.